The invention relates generally to an electric power grid and more specifically to load forecasting in the power grid.
A smart grid delivers electricity to consumers while leveraging digital communication technology to reduce cost, save energy, and increase reliability. If designed properly, the smart grid will have a significant impact on improving a wide range of aspects in the electric power generation and distribution industry. Examples include self-healing, high-reliability, resistance to cyber attack, accommodation of a wide variety of types of distributed generation and storage mechanisms, optimized asset allocation, and minimization of operation and maintenance expenses as well as high-resolution market control that incorporates advanced metering and demand-response.
Energy Management System (EMS) and Distribution Management System (DMS) are important components of the smart grid. EMS and DMS are utilized for providing capabilities to operate the bulk power system in a safe, reliable, and economic manner and further for developing new functions and capabilities for improving the reliability and efficiency of the distribution system. DMS uses load forecasting methodologies for distribution systems providing power to homes, commercial businesses, and industrial businesses. One of the methods of load forecasting is “similar day load forecasting”. In the similar day load forecasting approach, an operator is allowed to build and modify forecasts. Load forecasting approaches of this type which need human intervention can be time consuming. Further, human intervention is difficult to quantify and requires a certain amount of expertise.
Therefore, there is a need for an improved load forecasting method to address one or more aforementioned issues.